86 research outputs found

    Multiparametric Cardiac 18F-FDG PET in Humans: Kinetic Model Selection and Identifiability Analysis

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    Cardiac 18F-FDG PET has been used in clinics to assess myocardial glucose metabolism. Its ability for imaging myocardial glucose transport, however, has rarely been exploited in clinics. Using the dynamic FDG-PET scans of ten patients with coronary artery disease, we investigate in this paper appropriate dynamic scan and kinetic modeling protocols for efficient quantification of myocardial glucose transport. Three kinetic models and the effect of scan duration were evaluated by using statistical fit quality, assessing the impact on kinetic quantification, and analyzing the practical identifiability. The results show that the kinetic model selection depends on the scan duration. The reversible two-tissue model was needed for a one-hour dynamic scan. The irreversible two-tissue model was optimal for a scan duration of around 10 minutes. If the scan duration was shortened to 2 minutes, a one-tissue model was the most appropriate. For global quantification of myocardial glucose transport, we demonstrated that an early dynamic scan with a duration of 10 minutes and irreversible kinetic modeling was comparable to the full one-hour scan with reversible kinetic modeling. Myocardial glucose transport quantification provides an additional physiological parameter on top of the existing assessment of glucose metabolism, which may be used as a surrogate of myocardial blood flow to enable single tracer multiparametric imaging in the myocardium.Comment: 10 pages, 8 figure

    Treatment Planning and Volumetric Response Assessment for Yttrium-90 Radioembolization: Semiautomated Determination of Liver Volume and Volume of Tumor Necrosis in Patients with Hepatic Malignancy

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    PurposeThe primary purpose of this study was to demonstrate intraobserver/interobserver reproducibility for novel semiautomated measurements of hepatic volume used for Yttrium-90 dose calculations as well as whole-liver and necrotic-liver (hypodense/nonenhancing) tumor volume after radioembolization. The secondary aim was to provide initial comparisons of tumor volumetric measurements with linear measurements, as defined by Response Evaluation Criteria in Solid Tumors criteria, and survival outcomes.MethodsBetween 2006 and 2009, 23 consecutive radioembolization procedures were performed for 14 cases of hepatocellular carcinoma and 9 cases of hepatic metastases. Baseline and follow-up computed tomography obtained 1 month after treatment were retrospectively analyzed. Three observers measured liver, whole-tumor, and tumor-necrosis volumes twice using semiautomated software.ResultsGood intraobserver/interobserver reproducibility was demonstrated (intraclass correlation [ICC] > 0.9) for tumor and liver volumes. Semiautomated measurements of liver volumes were statistically similar to those obtained with manual tracing (ICC = 0.868), but they required significantly less time to perform (p < 0.0001, ICC = 0.088). There was a positive association between change in linear tumor measurements and whole-tumor volume (p < 0.0001). However, linear measurements did not correlate with volume of necrosis (p > 0.05). Dose, change in tumor diameters, tumor volume, and necrotic volume did not correlate with survival (p > 0.05 in all instances). However, Kaplan-Meier curves suggest that a >10% increase in necrotic volume correlated with survival (p = 0.0472).ConclusionSemiautomated volumetric analysis of liver, whole-tumor, and tumor-necrosis volume can be performed with good intraobserver/interobserver reproducibility. In this small retrospective study, measurements of tumor necrosis were suggested to correlate with survival

    Hiccups and bilateral carotid artery dissection

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    Theoretical study of the benefit of long axial field-of-view PET on region of interest quantification

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    The aim of this study is to evaluate the benefit of long axial field-of-view (AFOV) PET scanners on region of interest (ROI) quantification. We simulated a series of PET scanners with an AFOV ranging from 22 cm to 220 cm. A theoretical framework was used to predict the contrast recovery coefficient (CRC) and the variance of ROI quantification in penalized maximum likelihood (ML) image reconstruction, in which the resolution and noise tradeoff was controlled by a regularization parameter with a quadratic penalty function. The characterization was based on the converged penalized ML reconstruction with an accurate system model. We examined quantification of a 2 mm ROI and 10 mm ROI in a clinically relevant scan range of 110 cm. Multiple bed positions with 50% overlap were used for scanners with shorter AFOV to provide a relatively uniform sensitivity across the 110 cm axial range. A uniform water cylinder of 20 cm in diameter and 230 cm in length was chosen to model the attenuation and background activity. We computed the variance reduction factor at fixed resolution. Effects of different detector capabilities, including TOF (time-of-flight) resolution (320 ps, 500 ps, and non-TOF) and DOI (depth-of-interaction) resolution (4 mm, 10 mm, and no DOI), were evaluated. The results show that at a normal activity level (370 MBq), the 220 cm AFOV scanner offers a  ∼17-fold variance reduction for the 2 mm ROI and  ∼26-fold variance reduction for the 10 mm ROI (both measured at CRC  =  0.5) over the 22 cm AFOV scanner when both using detectors with 500 ps TOF resolution no DOI capability. The variance reduction factors of trues-only are higher than those of including scatters and randoms. Combining 320 ps TOF and 4 mm DOI, the 220 cm long scanner offers a  ∼45-fold variance reduction over the 22 cm long reference scanner (500 ps TOF, no DOI) for imaging 2 mm and 10 mm ROIs. The variance reduction factors are higher at a lower activity level due to lower random fraction. In conclusion, our study demonstrates that a long AFOV scanner can greatly improve the quantitative accuracy of PET imaging compared to current state-of-the-art clinical PET scanners

    Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET

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    Detecting cancerous lesions is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for the detection task and proposed a method to design a shift-invariant quadratic penalty function to maximize detectability of a lesion at a known location in a two dimensional image. Here we extend the regularization design to maximize detectability of lesions at unknown locations in fully 3D PET. We used a multiview channelized Hotelling observer (mvCHO) to assess the lesion detectability in 3D images to mimic the condition where a human observer examines three orthogonal views of a 3D image for lesion detection. We derived simplified theoretical expressions that allow fast prediction of the detectability of a 3D lesion. The theoretical results were used to design the regularization in PML reconstruction to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the optimized penalty with the conventional penalty for detecting lesions of various sizes. Only true coincidence events were simulated. Lesion detectability was also assessed by two human observers, whose performances agree well with that of the mvCHO. Both the numerical observer and human observer results showed a statistically significant improvement in lesion detection by using the proposed penalty function compared to using the conventional penalty function
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